Influence of Personnel Attributes on Revenue Collection Performance in Tanzanian LGAs: A Seemingly Unrelated Regression Analysis

This study investigates the effects of personnel attributes on revenue collection performance in Tanzanian Local Government Authorities (LGAs), focusing on Mbeya, Mwanza, and Manyara—categorized by the Controller and Auditor General (CAG) as high-, medium-, and low-performing councils, respectively. Rooted in Human Capital Theory, the study addresses the pressing issue of persistent revenue shortfalls—up to ۶۰% in some LGAs—linked to inadequate staff capacity, limited education, and insufficient job satisfaction. A cross-sectional survey was conducted among ۴۰۰ designated revenue officers using structured questionnaires. Data were analyzed using the Seemingly Unrelated Regression Model (SURM) to examine the simultaneous effects of multiple attributes on performance. The results revealed that education significantly increases revenue collection efficiency by ۰.۰۸۳–۰.۰۸۶ units (z = ۴.۸۸ to ۵.۳۸, p < ۰.۰۱), and experience contributes an improvement of ۰.۰۴۲–۰.۰۴۵ units (z = ۴.۵ to ۴.۸۹). Age has a positive effect, adding ۰.۰۱۲–۰.۰۱۴ units (z = ۴.۰ to ۴.۶۷), and job satisfaction enhances performance by ۰.۱۰۵–۰.۱۰۸ units (z = ۳.۷۵ to ۴.۰۸). Personnel capacity had the strongest effect, improving outcomes by ۰.۱۵–۰.۱۵۳ units (z = ۴.۰۵ to ۴.۳۱, p < ۰.۰۵), while job mobility showed moderate positive influence at ۰.۰۹۵–۰.۰۹۸ units (z = ۳.۸ to ۴.۱۷). Although performance incentives demonstrated mixed significance, the highest coefficient reached ۰.۶۷۵ (z = ۴.۸۷), suggesting some potential under targeted conditions. Notably, revenue officers aged over ۴۰ and with more than ۱۰ years of experience showed a ۱۵% higher reliability in meeting collection targets. The study concludes that enhancing staff competencies significantly boosts performance. It recommends targeted training for the ۴۰% of officers with only primary or secondary education, introduction of performance-based incentives, and establishment of job mobility schemes and mentorship programs to expand staff exposure and improve overall efficiency in local revenue administration.

کلیدواژه ها:

Local Government ، performance ، Revenue Collection ، Seemingly Unrelated Regression Model ، Tanzania